H. D. Koubodana, J. Adounkpe, Moustapha Tall, E. Amoussou, K. Atchonouglo, Muhammad Mumtaz
{"title":"Trend Analysis of Hydro-climatic Historical Data and Future Scenarios of Climate Extreme Indices over Mono River Basin in West Africa","authors":"H. D. Koubodana, J. Adounkpe, Moustapha Tall, E. Amoussou, K. Atchonouglo, Muhammad Mumtaz","doi":"10.12691/AJRD-8-1-5","DOIUrl":null,"url":null,"abstract":"Climate change impacts considerably on water balance components and needs to be evaluated through trend analysis or climate models scenarios extremes. The objective of this paper is to perform non-parametric Mann Kendall (MK) trend analysis on historical hydro-climatic data (1961-2016), to validate an ensemble climate model and to compute temperature and rainfall extremes indices. The climate indices are evaluated using MK test and annual trend analysis for two future scenarios (2020- 2045) over Mono River Basin (MRB) in Togo. Results show positive and negative trends of hydro-climatic data over MRB from 1961 to 2016. The average temperature increases significantly in most of the stations while a negative non-significant trend of rainfall is noticed. Meanwhile, the discharge presents a significant seasonal and annual trend Corrokope, Nangbeto and Athieme gauge stations. Validation of the ensemble climate models reveals that the model under-estimates observations at Sokode, Atkakpame and Tabligbo stations, however linear regression and spatial correlation coefficients are higher than 0.6. Moreover, the percentage of bias between climate model and observations are less than 15% at most of the stations. Finally, the computation of extreme climate indices under RCP4.5 and RCP8.5 scenarios shows a significant annual trend of some extreme climate indices of rainfall and temperature at selected stations between 2020 and 2045 in the MRB. Therefore, relevant governmental politics are needed to elaborate strategies and measures to cope with projected climate changes impacts in the country.","PeriodicalId":45379,"journal":{"name":"Journal of Rural and Community Development","volume":"37 1","pages":"37-52"},"PeriodicalIF":0.6000,"publicationDate":"2020-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Rural and Community Development","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12691/AJRD-8-1-5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"DEVELOPMENT STUDIES","Score":null,"Total":0}
引用次数: 10
Abstract
Climate change impacts considerably on water balance components and needs to be evaluated through trend analysis or climate models scenarios extremes. The objective of this paper is to perform non-parametric Mann Kendall (MK) trend analysis on historical hydro-climatic data (1961-2016), to validate an ensemble climate model and to compute temperature and rainfall extremes indices. The climate indices are evaluated using MK test and annual trend analysis for two future scenarios (2020- 2045) over Mono River Basin (MRB) in Togo. Results show positive and negative trends of hydro-climatic data over MRB from 1961 to 2016. The average temperature increases significantly in most of the stations while a negative non-significant trend of rainfall is noticed. Meanwhile, the discharge presents a significant seasonal and annual trend Corrokope, Nangbeto and Athieme gauge stations. Validation of the ensemble climate models reveals that the model under-estimates observations at Sokode, Atkakpame and Tabligbo stations, however linear regression and spatial correlation coefficients are higher than 0.6. Moreover, the percentage of bias between climate model and observations are less than 15% at most of the stations. Finally, the computation of extreme climate indices under RCP4.5 and RCP8.5 scenarios shows a significant annual trend of some extreme climate indices of rainfall and temperature at selected stations between 2020 and 2045 in the MRB. Therefore, relevant governmental politics are needed to elaborate strategies and measures to cope with projected climate changes impacts in the country.